DC Microgrid Control with Event-Triggered Photovoltaic Power Scanning for Improved Energy Storage Utilization Under Partial Shading

This paper proposes a photovoltaic (PV) power scanning aided hybrid control for dc microgrids (dcMGs) with PV and battery energy storage systems (BESSs). In contrast to existing dcMG controls, the proposed control reduces the BESS utilization for dc-link voltage regulation, even under partial shading conditions. To achieve this, a power-voltage (P-V) curve scanning mechanism is integrated within a flexible power point tracking algorithm, bypassing local maximum power points and matching the PV power to the demand. Compared to conventional periodic and full P-V curve scanning approaches, the proposed scanning is event-triggered and its range is adaptive by terminating the scan when a PV power that satisfies the demand is identified. The proposed control effectiveness is verified through simulations in MATLAB/Simulink.

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Publication Details

Published
2025-10-19
DOI
https://doi.org/10.1109/ecce58356.2025.11259571
Primary Topic
Microgrid Control and Optimization
Type
article
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article

DC Microgrid Control with Event-Triggered Photovoltaic Power Scanning for Improved Energy Storage Utilization Under Partial Shading

Josep Pou, Glen G. Farivar, Gaowen Liang, Hein Wai Yan et al.
Microgrid Control and Optimization
article

DC Microgrid Control with Event-Triggered Photovoltaic Power Scanning for Improved Energy Storage Utilization Under Partial Shading

Josep Pou, Glen G. Farivar, Gaowen Liang, Hein Wai Yan, Ezequiel Rodríguez
article en

Abstract

This paper proposes a photovoltaic (PV) power scanning aided hybrid control for dc microgrids (dcMGs) with PV and battery energy storage systems (BESSs). In contrast to existing dcMG controls, the proposed control reduces the BESS utilization for dc-link voltage regulation, even under partial shading conditions. To achieve this, a power-voltage (P-V) curve scanning mechanism is integrated within a flexible power point tracking algorithm, bypassing local maximum power points and matching the PV power to the demand. Compared to conventional periodic and full P-V curve scanning approaches, the proposed scanning is event-triggered and its range is adaptive by terminating the scan when a PV power that satisfies the demand is identified. The proposed control effectiveness is verified through simulations in MATLAB/Simulink.

The University of Melbourne (AU), City University of Hong Kong (HK), Nanyang Technological University (SG)
Openalex Percentile: Top 53%
Microgrid Control and Optimization
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